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A Content Based Image Retrieval Approach based on Multiple Multimedia Features Descriptors in E-health Environment

机译:电子医疗环境中基于多种多媒体特征描述符的基于内容的图像检索方法

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The extensive digitalization of biomedical images and the implementation of ad hoc digital infrastructures as Picture Archiving and Communication Systems (PACS) need of novel techniques to improve their effectiveness in different e-health tasks. The improvement of processing capabilities of the computer systems allows the use of more accurate techniques to analyze biomedical images. In this context, the image retrieval process represents a key activity. For this purpose, the use of Content Based Image Retrieval (CBIR) techniques on biomedical images repository could improve the effectiveness in specific biomedical image retrieval and support the human decision making process. The aim of our paper is to implement a CBIR system based on local, global and novel deep descriptors extracted from images and compared to prove their efficiency in a real e-health scenario. Several experiments have been carried out using a real dataset and standard measures to show the effectiveness of our approach.
机译:生物医学图像的广泛数字化以及作为图片存档和通信系统(PACS)的临时数字基础设施的实现,需要新颖的技术来提高其在不同的电子卫生任务中的有效性。计算机系统处理能力的提高允许使用更准确的技术来分析生物医学图像。在这种情况下,图像检索过程代表了一项关键活动。为此,在生物医学图像存储库上使用基于内容的图像检索(CBIR)技术可以提高特定生物医学图像检索的有效性,并支持人类决策过程。本文的目的是基于从图像中提取的局部,全局和新颖的深层描述符来实现CBIR系统,并进行比较以证明其在实际电子医疗场景中的效率。使用真实的数据集和标准方法进行了几次实验,以证明我们方法的有效性。

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